Classical ML
SMOTE
Synthetic Minority Over-sampling: creates new minority examples by interpolating between a point and its k nearest minority neighbours.
Why interviewers ask about it
Frequently hurts in high dimensions, where interpolated points fall in majority territory. Always measure PR-AUC before and after, and remember it destroys calibration.
Related terms
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